A Task Allocation and Performance Analysis Based on Finished Time

Qu Shaogang, Yang Guangwen, Lin Chuang, and Shi Shuming

Journal of Computer Research and Development > 2005 > 42(8): 1397-1402.

Qu Shaogang, Yang Guangwen, Lin Chuang, and Shi Shuming. A Task Allocation and Performance Analysis Based on Finished Time[J]. Journal of Computer Research and Development, 2005, 42(8): 1397-1402.

Citation:

Qu Shaogang, Yang Guangwen, Lin Chuang, and Shi Shuming. A Task Allocation and Performance Analysis Based on Finished Time[J]. Journal of Computer Research and Development, 2005, 42(8): 1397-1402.

Citation:

Qu Shaogang, Yang Guangwen, Lin Chuang, and Shi Shuming. A Task Allocation and Performance Analysis Based on Finished Time[J]. Journal of Computer Research and Development, 2005, 42(8): 1397-1402.

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A Task Allocation and Performance Analysis Based on Finished Time

Qu Shaogang, Yang Guangwen, Lin Chuang, and Shi Shuming

(Department of Computer Science and Technology, Tsinghua University, Beijing 100084)

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Published Date: August 14, 2005

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Abstract

Abstract

Seemingly overnight, the Internet has gone from an academic experiment to a worldwide information matrix. How to improve the response time and throughput of a complicated network system is a challenging problem. Discussed and provided in this paper are quest dispatching and selecting schemes for Web server clusters and the stochastic high level Petrinet models for those schemes. A novel method is proposed to allocate Web request tasks according to the minimums finished time and an analysis is also presented based on the experiments using Petri net. Experiment results show that the method is feasible and effective.
- request select,
- request allocation,
- Petri net

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[3]	Yu Chang, Wang Yawen, Lin Huan, Gong Yunzhan. Fault Detection Context Based Equivalent Mutant Identification Algorithm[J]. Journal of Computer Research and Development, 2021, 58(1): 83-97. DOI: 10.7544/issn1000-1239.2021.20190817
[4]	Lin Xin, Tian Xin, Ji Yi, Xu Yunlong, Liu Chunping. Scene Graph Generation Based on Shuffle Residual Context Information[J]. Journal of Computer Research and Development, 2019, 56(8): 1721-1730. DOI: 10.7544/issn1000-1239.2019.20190329
[5]	Yang Qian, Luo Juan, Liu Chang. Context Based Service Recommendation Middleware in VANET[J]. Journal of Computer Research and Development, 2017, 54(9): 1992-2000. DOI: 10.7544/issn1000-1239.2017.20160640
[6]	Chen Xiaokang, Xu Chang, Jiang Lei. Hybrid-Fixing: Toward Sound Fixing of Context Inconsistency[J]. Journal of Computer Research and Development, 2015, 52(6): 1443-1451. DOI: 10.7544/issn1000-1239.2015.20131904
[7]	Li Weijiang, Zhao Tiejun, Wang Xiangang. Context-Sensitive Query Expansion[J]. Journal of Computer Research and Development, 2010, 47(2): 300-304.
[8]	Lin Xin, Li Shanping, Yang Zhaohui, Xu Jian. A Reasoning-Oriented Context Replacement Algorithm in Pervasive Computing[J]. Journal of Computer Research and Development, 2009, 46(4): 549-557.
[9]	Tang Lei, Huai Xiaoyong, Li Mingshu. An Approach to Dynamic Service Composition Based on Context Negotiation[J]. Journal of Computer Research and Development, 2008, 45(11): 1902-1910.
[10]	Li Rui and Li Renfa. A Survey of Context-Aware Computing and Its System Infrastructure[J]. Journal of Computer Research and Development, 2007, 44(2): 269-276.